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A Non-Monotone Trust Region Method with Non-Monotone Wolfe-Type Line Search Strategy for Unconstrained Optimization

机译:非单调沃尔夫型线搜索策略的非单调信赖域方法无约束优化

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In this paper, we propose and analyze a non-monotone trust region method with non-monotone line search strategy for unconstrained optimization problems. Unlike the traditional non-monotone trust region method, our algorithm utilizes non-monotone Wolfe line search to get the next point if a trial step is not adopted. Thus, it can reduce the number of solving sub-problems. Theoretical analysis shows that the new proposed method has a global convergence under some mild conditions.
机译:在本文中,我们提出并分析了一种用于非约束优化问题的具有非单调线搜索策略的非单调信赖域方法。与传统的非单调信任域方法不同,如果不采用试验步骤,我们的算法将利用非单调Wolfe线搜索来获取下一个点。因此,它可以减少求解子问题的数量。理论分析表明,该新方法在一定的温和条件下具有全局收敛性。

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